Temperature interpolation at a large scale: test on a small area in Svalbard

Abstract

A major environmental concern regarding the Arctic is how global change effects can influence vegetation and ecosystems. The amount of summer warmth is the single most important variable for biological processes in the Arctic, and the one that is most likely to be affected by climate change. A major task is to establish how temperature conditions are modified at a very high spatial resolution.In order to build up scenarios that are as relevant as possible concerning vegetation development, the key point is to know how the spatial distribution of temperature varies and can be related to different environment factors at different spatial scales. A method is suggested for modelling the temperature distribution at a high resolution (2 × 2 m 2 ) and with high accuracy. In step one, a polynomial equation is established for modelling the distribution of temperature values measured in the field at low spatial resolution (1 × 1 km 2 ), with latitude and longitude defining the general trend surface of the temperature distribution. In step two, residue values from the previous step are explained by environment factors stored as numerical information layers in a geographical information system. These environmental data are derived from a high-resolution digital elevation model and from a digitized infrared aerial photograph. Finally, the combination of these kilometric and micro-scale models make it possible to restore the thermic field of the study area and to represent it through different maps at a very fine-grained resolution. The method is tested on two glacier forefields in Svalbard, covering an area of 8 km 2 .

Spatial interpolation‐based mapping of the spring frost hazard in the Champagne vineyards

“…In order to take into account phenomena at different scales, the topographic parameters were computed according to several spatial windows (Joly et al 2003; see Figure 3). …”

Paraglacial gullying of sediment‐mantled slopes: a case study of Colletthøgda, Kongsfjorden area, West Spitsbergen (Svalbard)

“…Intense rainfall is rare during summer time while prolonged rainfall is more common (Mercier, 2001). Temperature measurements all over the Kongsfjorden area have shown that the warmest places are located in lee-side areas and the coldest areas are situated near glacier fronts, where katabatic winds contribute to continuous air fl ow (Brossard et al, 2002;Joly et al, 2003;Joly, 2004).…”

Temperature interpolation based on local information: the example of France

“…The first two interpolation methods we use are a statistical method based on regressions (Cressie, 1993;Joly et al, 2003), and a probabilistic method, ordinary kriging (Matheron, 1970;Courault and Monestiez, 1999;Baillargeon, 2005). It is worth going over their respective advantages and drawbacks.…”